Abstract

Info

Title:: Psychological pressure detection system based on BP network and IoMT

Author(s):: MENG Fanchen; CAO Le; KAN Xiu; ZHANG Lei; TIAN Jianpeng; School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China

Keywords:: Keywords: psychological pressure back propagation neural network feature extraction internet of medical things heart rate variability

Abstract:: Abstract: In order to improve the accuracy of classification results of human psychological pressure measurement based on pulse signal, a psychological pressure detection system based on back propagation network and internet of medical things (IoMT) is proposed. The system uses the photoplethysmography (PPG) acquisition module with MAX30101 as the core to acquire human PPG data, and obtains ventricular beat-to-beat interval based on wavelet denoising and RR peak detection. The heart rate variability extracted by processing in time and frequency domains is taken as the feature, and a back propagation neural network model trained by Adam adaptive optimization algorithm is established to classify the degree of psychological pressure into 3 categories. At the same time, a remote platform based on IoMT for psychological pressure detection is designed for 24-hour continuous user health monitoring, thereby achieving long-term uninterrupted detection and analysis. The experimental results show that the system has a detection accuracy of 88.7%, and that it is more effective and convenient to classify the degree of psychological stress than traditional psychological scale and hormone measurement.